spaCy/website/docs/api/morphology.mdx

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---
title: Morphology
tag: class
source: spacy/morphology.pyx
---
Store the possible morphological analyses for a language, and index them by
hash. To save space on each token, tokens only know the hash of their
morphological analysis, so queries of morphological attributes are delegated to
this class. See [`MorphAnalysis`](/api/morphology#morphanalysis) for the
container storing a single morphological analysis.
## Morphology.\_\_init\_\_ {id="init",tag="method"}
Create a `Morphology` object.
> #### Example
>
> ```python
> from spacy.morphology import Morphology
>
> morphology = Morphology(strings)
> ```
| Name | Description |
| --------- | --------------------------------- |
| `strings` | The string store. ~~StringStore~~ |
## Morphology.add {id="add",tag="method"}
Insert a morphological analysis in the morphology table, if not already present.
The morphological analysis may be provided in the Universal Dependencies
[FEATS](https://universaldependencies.org/format.html#morphological-annotation)
format as a string or in the tag map dictionary format. Returns the hash of the
new analysis.
> #### Example
>
> ```python
> feats = "Feat1=Val1|Feat2=Val2"
> hash = nlp.vocab.morphology.add(feats)
> assert hash == nlp.vocab.strings[feats]
> ```
| Name | Description |
| ---------- | ------------------------------------------------ |
| `features` | The morphological features. ~~Union[Dict, str]~~ |
## Morphology.get {id="get",tag="method"}
> #### Example
>
> ```python
> feats = "Feat1=Val1|Feat2=Val2"
> hash = nlp.vocab.morphology.add(feats)
> assert nlp.vocab.morphology.get(hash) == feats
> ```
Get the
[FEATS](https://universaldependencies.org/format.html#morphological-annotation)
string for the hash of the morphological analysis.
| Name | Description |
| ------- | ----------------------------------------------- |
| `morph` | The hash of the morphological analysis. ~~int~~ |
## Morphology.feats_to_dict {id="feats_to_dict",tag="staticmethod"}
Convert a string
[FEATS](https://universaldependencies.org/format.html#morphological-annotation)
representation to a dictionary of features and values in the same format as the
tag map.
> #### Example
>
> ```python
> from spacy.morphology import Morphology
> d = Morphology.feats_to_dict("Feat1=Val1|Feat2=Val2")
> assert d == {"Feat1": "Val1", "Feat2": "Val2"}
> ```
| Name | Description |
| ----------- | ---------------------------------------------------------------------------------------------------------------------------------------------------- |
| `feats` | The morphological features in Universal Dependencies [FEATS](https://universaldependencies.org/format.html#morphological-annotation) format. ~~str~~ |
| **RETURNS** | The morphological features as a dictionary. ~~Dict[str, str]~~ |
## Morphology.dict_to_feats {id="dict_to_feats",tag="staticmethod"}
Convert a dictionary of features and values to a string
[FEATS](https://universaldependencies.org/format.html#morphological-annotation)
representation.
> #### Example
>
> ```python
> from spacy.morphology import Morphology
> f = Morphology.dict_to_feats({"Feat1": "Val1", "Feat2": "Val2"})
> assert f == "Feat1=Val1|Feat2=Val2"
> ```
| Name | Description |
| ------------ | ---------------------------------------------------------------------------------------------------------------------------------------------------- |
| `feats_dict` | The morphological features as a dictionary. ~~Dict[str, str]~~ |
| **RETURNS** | The morphological features in Universal Dependencies [FEATS](https://universaldependencies.org/format.html#morphological-annotation) format. ~~str~~ |
## Attributes {id="attributes"}
| Name | Description |
| ------------- | ------------------------------------------------------------------------------------------------------------------------------- |
| `FEATURE_SEP` | The [FEATS](https://universaldependencies.org/format.html#morphological-annotation) feature separator. Default is `\|`. ~~str~~ |
| `FIELD_SEP` | The [FEATS](https://universaldependencies.org/format.html#morphological-annotation) field separator. Default is `=`. ~~str~~ |
| `VALUE_SEP` | The [FEATS](https://universaldependencies.org/format.html#morphological-annotation) value separator. Default is `,`. ~~str~~ |
## MorphAnalysis {id="morphanalysis",tag="class",source="spacy/tokens/morphanalysis.pyx"}
Stores a single morphological analysis.
### MorphAnalysis.\_\_init\_\_ {id="morphanalysis-init",tag="method"}
Initialize a MorphAnalysis object from a Universal Dependencies
[FEATS](https://universaldependencies.org/format.html#morphological-annotation)
string or a dictionary of morphological features.
> #### Example
>
> ```python
> from spacy.tokens import MorphAnalysis
>
> feats = "Feat1=Val1|Feat2=Val2"
> m = MorphAnalysis(nlp.vocab, feats)
> ```
| Name | Description |
| ---------- | ---------------------------------------------------------- |
| `vocab` | The vocab. ~~Vocab~~ |
| `features` | The morphological features. ~~Union[Dict[str, str], str]~~ |
### MorphAnalysis.\_\_contains\_\_ {id="morphanalysis-contains",tag="method"}
Whether a feature/value pair is in the analysis.
> #### Example
>
> ```python
> feats = "Feat1=Val1,Val2|Feat2=Val2"
> morph = MorphAnalysis(nlp.vocab, feats)
> assert "Feat1=Val1" in morph
> ```
| Name | Description |
| ----------- | --------------------------------------------- |
| **RETURNS** | A feature/value pair in the analysis. ~~str~~ |
### MorphAnalysis.\_\_iter\_\_ {id="morphanalysis-iter",tag="method"}
Iterate over the feature/value pairs in the analysis.
> #### Example
>
> ```python
> feats = "Feat1=Val1,Val3|Feat2=Val2"
> morph = MorphAnalysis(nlp.vocab, feats)
> assert list(morph) == ["Feat1=Va1", "Feat1=Val3", "Feat2=Val2"]
> ```
| Name | Description |
| ---------- | --------------------------------------------- |
| **YIELDS** | A feature/value pair in the analysis. ~~str~~ |
### MorphAnalysis.\_\_len\_\_ {id="morphanalysis-len",tag="method"}
Returns the number of features in the analysis.
> #### Example
>
> ```python
> feats = "Feat1=Val1,Val2|Feat2=Val2"
> morph = MorphAnalysis(nlp.vocab, feats)
> assert len(morph) == 3
> ```
| Name | Description |
| ----------- | ----------------------------------------------- |
| **RETURNS** | The number of features in the analysis. ~~int~~ |
### MorphAnalysis.\_\_str\_\_ {id="morphanalysis-str",tag="method"}
Returns the morphological analysis in the Universal Dependencies
[FEATS](https://universaldependencies.org/format.html#morphological-annotation)
string format.
> #### Example
>
> ```python
> feats = "Feat1=Val1,Val2|Feat2=Val2"
> morph = MorphAnalysis(nlp.vocab, feats)
> assert str(morph) == feats
> ```
| Name | Description |
| ----------- | ------------------------------------------------------------------------------------------------------------------------------------------ |
| **RETURNS** | The analysis in the Universal Dependencies [FEATS](https://universaldependencies.org/format.html#morphological-annotation) format. ~~str~~ |
### MorphAnalysis.get {id="morphanalysis-get",tag="method"}
Retrieve values for a feature by field.
> #### Example
>
> ```python
> feats = "Feat1=Val1,Val2"
> morph = MorphAnalysis(nlp.vocab, feats)
> assert morph.get("Feat1") == ["Val1", "Val2"]
> ```
| Name | Description |
| ----------- | ------------------------------------------------ |
| `field` | The field to retrieve. ~~str~~ |
| **RETURNS** | A list of the individual features. ~~List[str]~~ |
### MorphAnalysis.to_dict {id="morphanalysis-to_dict",tag="method"}
Produce a dict representation of the analysis, in the same format as the tag
map.
> #### Example
>
> ```python
> feats = "Feat1=Val1,Val2|Feat2=Val2"
> morph = MorphAnalysis(nlp.vocab, feats)
> assert morph.to_dict() == {"Feat1": "Val1,Val2", "Feat2": "Val2"}
> ```
| Name | Description |
| ----------- | ----------------------------------------------------------- |
| **RETURNS** | The dict representation of the analysis. ~~Dict[str, str]~~ |
### MorphAnalysis.from_id {id="morphanalysis-from_id",tag="classmethod"}
Create a morphological analysis from a given hash ID.
> #### Example
>
> ```python
> feats = "Feat1=Val1|Feat2=Val2"
> hash = nlp.vocab.strings[feats]
> morph = MorphAnalysis.from_id(nlp.vocab, hash)
> assert str(morph) == feats
> ```
| Name | Description |
| ------- | ---------------------------------------- |
| `vocab` | The vocab. ~~Vocab~~ |
| `key` | The hash of the features string. ~~int~~ |